code: def get_ckpt_name(
      model="resnet",
      optimizer="sgd",
      lr=0.1,
      final_lr=0.1,
      momentum=0.9,
      beta1=0.9,
      beta2=0.999,
      gamma=1e-3,
  ):
      name = {
          "sgd": "lr{}-momentum{}".format(lr, momentum),
          "adagrad": "lr{}".format(lr),
          "adam": "lr{}-betas{}-{}".format(lr, beta1, beta2),
          "amsgrad": "lr{}-betas{}-{}".format(lr, beta1, beta2),
          "adabound": "lr{}-betas{}-{}-final_lr{}-gamma{}".format(
              lr, beta1, beta2, final_lr, gamma
          ),
          "amsbound": "lr{}-betas{}-{}-final_lr{}-gamma{}".format(
              lr, beta1, beta2, final_lr, gamma
          ),
      }[optimizer]
      return "{}-{}-{}".format(model, optimizer, name)
  
file_path: AdaBound/demos/cifar10/main.py
imports: from __future__ import print_function
  import torch.optim
  import torch.backends.cudnn
  import torchvision
  import torchvision.transforms
  import os
  import argparse
  from models import *
  from adabound import AdaBound
label_desc: Use image node_id 3 for calling a global function with example usage: get_ckpt_name(model, optimizer, lr, final_lr, momentum, beta1, beta2, gamma) and returns: str